The present invention relates to machine aided writing systems and methods. In particular, the present invention relates to systems and methods for aiding users in writing in non-native languages.
With the rapid development of global communications, the ability to write in English and other non-native languages is becoming more important. However, non-native speakers (for example, people who speak Chinese, Japanese, Korean or other non-English languages) often find it very difficult to write in English. The difficulty is frequently not in spelling, nor in grammar, but in idiomatic usage. Therefore, the biggest problem for these non-natives while writing in English is determining how to polish sentences. While this can be true regarding the process of writing in any non-native language, the problem is described primarily with reference to English writing.
Spelling check and grammar check are helpful only when the user misspells a word or makes an obvious grammar mistake. These checking programs cannot be depended on for help in polishing sentences. A dictionary can be helpful as well, but mostly only for resolving reading and translation issues. Normally, looking up a word in a dictionary provides the writer with multiple explanations about the usages of the word, but without contextual information. As a result, it's too confusing and time-consuming for users to get any solution.
Generally, writers find it very helpful to have good example sentences available while writing for reference in polishing sentences. The problem is that those example sentences are hardly available at hand. In addition, up to now, no effective software has existed that supports English polish, and it is believed that few researchers have ever worked on this area.
There are numerous challenges to realizing a system capable of aiding users in polishing English sentences. First, given a user's sentence, it must be determined how to retrieve confirming sentences. Confirming sentences are used to confirm the user's sentences. Confirming sentences should be close in sentence structure or form to the user's input query or intended input query. Given a limited example base, it is hard to retrieve totally similar sentences, so it is typically only possible to retrieve sentences containing some similar parts to the sentence being written (the query sentence). Then, two interrelated questions arise. The first question is that if the user's sentence is too long and complex, which part should be taken as the user's focus? The second question is that if a large number of sentences are matched, how can or should they be ranked precisely and efficiently in order to maximize their usefulness to the writer?
A second challenge is determining how to retrieve hint sentences. Hint sentences are used to provide expanded expressions. In other words, hint sentences should be similar in meaning to the user's input query sentence, and are used to provide the user with alternate ways to express a particular idea. A more complicated case is determining how to detect the user's real intention, in order to retrieve appropriate hint sentences, when the user's sentence contains confusing expressions, or even if the user's sentence is written in English but employs a sentence structure or grammar appropriate for another language (for example, a “Chinese-like English sentence”). A third challenge relates to the fact that a user may search with a query written in his or her native language. To realize a precise translation, query understanding and translation selection are two big technical obstacles.
Although the aforementioned problems are described with reference to English language writing by people for whom English is not their native language (for example, native Chinese, Japanese or Korean speaking people), these problems are common for people who are writing in a first (non-native) language, but who are native speakers of a second (native) language. In light of these problems, or others not discussed, a system or method which aids non-native speakers in writing in English or other non-native languages by providing relevant confirming and/or hint sentences would be a significant improvement in the art.